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Somphone Siviengphanom
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2020 – today
- 2025
[j2]Somphone Siviengphanom
, Patrick C. Brennan, Sarah J. Lewis, Phuong Dung Trieu, Ziba Gandomkar
:
A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult. J. Imaging Inform. Medicine 38(3): 1904-1913 (2025)- 2023
[j1]Somphone Siviengphanom
, Ziba Gandomkar
, Sarah J. Lewis, Patrick C. Brennan:
Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases. J. Digit. Imaging 36(4): 1541-1552 (2023)
[c5]Ziba Gandomkar
, Sarah J. Lewis, Somphone Siviengphanom, Dennis Wong, Ernest U. Ekpo, Moayyad E. Suleiman
, Xuetong Tao, Warren M. Reed
, Patrick C. Brennan:
False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammograms. Image Perception, Observer Performance, and Technology Assessment 2023
[c4]Somphone Siviengphanom, Ziba Gandomkar
, Sarah J. Lewis, Patrick C. Brennan:
Global mammographic radiomic signature can predict radiologists' difficult-to-interpret normal cases. Image Perception, Observer Performance, and Technology Assessment 2023
[c3]Xuetong Tao, Somphone Siviengphanom, Ziba Gandomkar
, Tong Li
, Warren M. Reed
, Patrick C. Brennan:
Investigating the error-making patterns in reading high-density screening mammograms between radiologists from two countries. Image Perception, Observer Performance, and Technology Assessment 2023- 2022
[c2]Ziba Gandomkar
, Somphone Siviengphanom, Moayyad E. Suleiman
, Dennis Wong, Warren M. Reed
, Ernest U. Ekpo, Dong Xu, Sarah J. Lewis
, Patrick C. Brennan:
The reliability of radiologists' first impression interpreting a screening mammogram. Image Perception, Observer Performance, and Technology Assessment 2022- 2021
[c1]Ziba Gandomkar
, Ernest U. Ekpo, Sarah J. Lewis
, Moayyad E. Suleiman
, Somphone Siviengphanom, Tong Li
, Patrick C. Brennan:
An end-to-end deep learning model can detect the gist of the abnormal in prior mammograms as perceived by experienced radiologists. Image Perception, Observer Performance, and Technology Assessment 2021
Coauthor Index

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